from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 13.0 | 35.778080 |
| daal4py_KNeighborsClassifier | 0.0 | 3.0 | 5.774728 |
| KNeighborsClassifier_kd_tree | 0.0 | 6.0 | 56.388870 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 46.176190 |
| KMeans_tall | 0.0 | 1.0 | 38.758315 |
| daal4py_KMeans_tall | 0.0 | 1.0 | 14.115780 |
| KMeans_short | 0.0 | 0.0 | 16.751806 |
| daal4py_KMeans_short | 0.0 | 0.0 | 7.513559 |
| LogisticRegression | 0.0 | 1.0 | 2.259433 |
| daal4py_LogisticRegression | 0.0 | 0.0 | 54.962842 |
| Ridge | 0.0 | 0.0 | 46.445934 |
| daal4py_Ridge | 0.0 | 0.0 | 14.037203 |
| total | 0.0 | 31.0 | 39.032567 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.136 | 0.001 | 1000000 | 1000000 | 100 | brute | -1 | 1 | NaN | NaN | 0.466 | 0.002 | 0.292 | 0.003 | See |
| 1 | KNeighborsClassifier | predict | 0.164 | 0.012 | 1000000 | 1 | 100 | brute | -1 | 1 | 1.0 | 0.0 | 0.089 | 0.001 | 1.846 | 0.141 | See |
| 2 | KNeighborsClassifier | predict | 28.998 | 0.687 | 1000000 | 1000 | 100 | brute | -1 | 1 | 1.0 | 0.0 | 1.805 | 0.015 | 16.065 | 0.402 | See |
| 3 | KNeighborsClassifier | fit | 0.133 | 0.003 | 1000000 | 1000000 | 100 | brute | -1 | 5 | NaN | NaN | 0.469 | 0.004 | 0.284 | 0.006 | See |
| 4 | KNeighborsClassifier | predict | 0.172 | 0.012 | 1000000 | 1 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 0.089 | 0.001 | 1.935 | 0.134 | See |
| 5 | KNeighborsClassifier | predict | 36.367 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 1.809 | 0.012 | 20.107 | 0.138 | See |
| 6 | KNeighborsClassifier | fit | 0.123 | 0.001 | 1000000 | 1000000 | 100 | brute | -1 | 100 | NaN | NaN | 0.468 | 0.002 | 0.263 | 0.003 | See |
| 7 | KNeighborsClassifier | predict | 0.169 | 0.010 | 1000000 | 1 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 0.090 | 0.001 | 1.881 | 0.117 | See |
| 8 | KNeighborsClassifier | predict | 36.398 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 1.851 | 0.009 | 19.668 | 0.097 | See |
| 9 | KNeighborsClassifier | fit | 0.123 | 0.000 | 1000000 | 1000000 | 100 | brute | 1 | 1 | NaN | NaN | 0.468 | 0.003 | 0.262 | 0.002 | See |
| 10 | KNeighborsClassifier | predict | 0.178 | 0.001 | 1000000 | 1 | 100 | brute | 1 | 1 | 1.0 | 0.0 | 0.089 | 0.001 | 2.010 | 0.031 | See |
| 11 | KNeighborsClassifier | predict | 13.116 | 0.026 | 1000000 | 1000 | 100 | brute | 1 | 1 | 1.0 | 0.0 | 1.807 | 0.013 | 7.260 | 0.055 | See |
| 12 | KNeighborsClassifier | fit | 0.123 | 0.001 | 1000000 | 1000000 | 100 | brute | 1 | 5 | NaN | NaN | 0.470 | 0.001 | 0.261 | 0.001 | See |
| 13 | KNeighborsClassifier | predict | 0.188 | 0.001 | 1000000 | 1 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 0.091 | 0.001 | 2.066 | 0.023 | See |
| 14 | KNeighborsClassifier | predict | 22.592 | 0.014 | 1000000 | 1000 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 1.810 | 0.007 | 12.483 | 0.049 | See |
| 15 | KNeighborsClassifier | fit | 0.122 | 0.001 | 1000000 | 1000000 | 100 | brute | 1 | 100 | NaN | NaN | 0.475 | 0.004 | 0.257 | 0.003 | See |
| 16 | KNeighborsClassifier | predict | 0.189 | 0.001 | 1000000 | 1 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 0.089 | 0.000 | 2.130 | 0.012 | See |
| 17 | KNeighborsClassifier | predict | 22.648 | 0.035 | 1000000 | 1000 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 1.872 | 0.020 | 12.096 | 0.131 | See |
| 18 | KNeighborsClassifier | fit | 0.059 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 1 | NaN | NaN | 0.100 | 0.002 | 0.592 | 0.012 | See |
| 19 | KNeighborsClassifier | predict | 0.020 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.005 | 0.000 | 3.744 | 0.480 | See |
| 20 | KNeighborsClassifier | predict | 24.746 | 0.186 | 1000000 | 1000 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.263 | 0.002 | 94.089 | 0.971 | See |
| 21 | KNeighborsClassifier | fit | 0.055 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 5 | NaN | NaN | 0.098 | 0.002 | 0.565 | 0.012 | See |
| 22 | KNeighborsClassifier | predict | 0.030 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.005 | 0.001 | 5.832 | 0.796 | See |
| 23 | KNeighborsClassifier | predict | 31.623 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.266 | 0.001 | 118.988 | 0.545 | See |
| 24 | KNeighborsClassifier | fit | 0.055 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 100 | NaN | NaN | 0.097 | 0.000 | 0.573 | 0.006 | See |
| 25 | KNeighborsClassifier | predict | 0.029 | 0.001 | 1000000 | 1 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.006 | 0.001 | 5.215 | 0.609 | See |
| 26 | KNeighborsClassifier | predict | 31.846 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.313 | 0.002 | 101.801 | 0.720 | See |
| 27 | KNeighborsClassifier | fit | 0.055 | 0.000 | 1000000 | 1000000 | 2 | brute | 1 | 1 | NaN | NaN | 0.098 | 0.002 | 0.567 | 0.013 | See |
| 28 | KNeighborsClassifier | predict | 0.015 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.005 | 0.000 | 2.910 | 0.250 | See |
| 29 | KNeighborsClassifier | predict | 10.391 | 0.028 | 1000000 | 1000 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.267 | 0.003 | 38.987 | 0.516 | See |
| 30 | KNeighborsClassifier | fit | 0.057 | 0.000 | 1000000 | 1000000 | 2 | brute | 1 | 5 | NaN | NaN | 0.099 | 0.001 | 0.582 | 0.007 | See |
| 31 | KNeighborsClassifier | predict | 0.025 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.006 | 0.000 | 4.585 | 0.397 | See |
| 32 | KNeighborsClassifier | predict | 17.989 | 0.035 | 1000000 | 1000 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.265 | 0.003 | 67.801 | 0.673 | See |
| 33 | KNeighborsClassifier | fit | 0.055 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 100 | NaN | NaN | 0.098 | 0.003 | 0.565 | 0.016 | See |
| 34 | KNeighborsClassifier | predict | 0.026 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.006 | 0.000 | 4.650 | 0.418 | See |
| 35 | KNeighborsClassifier | predict | 17.998 | 0.045 | 1000000 | 1000 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.313 | 0.003 | 57.480 | 0.528 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 3.188 | 0.053 | 1000000 | 1000000 | 10 | kd_tree | -1 | 1 | NaN | NaN | 0.739 | 0.009 | 4.312 | 0.090 | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 8.385 | 4.505 | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.474 | 0.006 | 1000000 | 1000 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.128 | 0.003 | 3.705 | 0.097 | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 3.154 | 0.056 | 1000000 | 1000000 | 10 | kd_tree | -1 | 5 | NaN | NaN | 0.776 | 0.011 | 4.064 | 0.092 | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 6.928 | 4.973 | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.949 | 0.015 | 1000000 | 1000 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.222 | 0.002 | 4.280 | 0.083 | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 3.232 | 0.133 | 1000000 | 1000000 | 10 | kd_tree | -1 | 100 | NaN | NaN | 0.767 | 0.020 | 4.216 | 0.205 | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.004 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 5.587 | 2.753 | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 3.081 | 0.028 | 1000000 | 1000 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.689 | 0.006 | 4.473 | 0.057 | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 3.125 | 0.057 | 1000000 | 1000000 | 10 | kd_tree | 1 | 1 | NaN | NaN | 0.792 | 0.009 | 3.945 | 0.085 | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 2.334 | 1.836 | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.832 | 0.006 | 1000000 | 1000 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.128 | 0.002 | 6.475 | 0.102 | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 3.128 | 0.051 | 1000000 | 1000000 | 10 | kd_tree | 1 | 5 | NaN | NaN | 0.768 | 0.019 | 4.073 | 0.121 | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 2.594 | 1.756 | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1.639 | 0.016 | 1000000 | 1000 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.226 | 0.005 | 7.252 | 0.178 | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 3.184 | 0.044 | 1000000 | 1000000 | 10 | kd_tree | 1 | 100 | NaN | NaN | 0.778 | 0.010 | 4.090 | 0.078 | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 2.598 | 1.583 | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 5.487 | 0.073 | 1000000 | 1000 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.650 | 0.010 | 8.443 | 0.173 | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1.245 | 0.021 | 1000000 | 1000000 | 2 | kd_tree | -1 | 1 | NaN | NaN | 0.472 | 0.017 | 2.640 | 0.105 | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 18.757 | 16.927 | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.025 | 0.000 | 1000000 | 1000 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 32.283 | 15.549 | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1.225 | 0.021 | 1000000 | 1000000 | 2 | kd_tree | -1 | 5 | NaN | NaN | 0.455 | 0.004 | 2.689 | 0.052 | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 17.383 | 16.171 | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.027 | 0.001 | 1000000 | 1000 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 24.498 | 9.699 | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1.251 | 0.034 | 1000000 | 1000000 | 2 | kd_tree | -1 | 100 | NaN | NaN | 0.457 | 0.005 | 2.735 | 0.080 | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 17.586 | 15.106 | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.047 | 0.001 | 1000000 | 1000 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.006 | 0.001 | 7.367 | 0.876 | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1.274 | 0.028 | 1000000 | 1000000 | 2 | kd_tree | 1 | 1 | NaN | NaN | 0.460 | 0.008 | 2.771 | 0.077 | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 5.711 | 5.554 | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.024 | 0.000 | 1000000 | 1000 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 32.123 | 14.855 | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1.265 | 0.025 | 1000000 | 1000000 | 2 | kd_tree | 1 | 5 | NaN | NaN | 0.460 | 0.007 | 2.749 | 0.069 | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 5.553 | 5.408 | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.026 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 23.215 | 8.228 | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1.246 | 0.036 | 1000000 | 1000000 | 2 | kd_tree | 1 | 100 | NaN | NaN | 0.459 | 0.004 | 2.714 | 0.082 | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 4.830 | 4.153 | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.054 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.006 | 0.001 | 8.433 | 0.766 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 0.574 | 0.009 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.417 | 0.034 | 1.375 | 0.115 | See |
| 1 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.938 | 1.792 | See |
| 2 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.750 | 1.376 | See |
| 3 | KMeans_tall | fit | 0.496 | 0.004 | 1000000 | 1000000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.376 | 0.028 | 1.318 | 0.100 | See |
| 4 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.845 | 1.644 | See |
| 5 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.667 | 1.347 | See |
| 6 | KMeans_tall | fit | 6.312 | 0.083 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 2.960 | 0.027 | 2.132 | 0.034 | See |
| 7 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.786 | 1.489 | See |
| 8 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.166 | 1.662 | See |
| 9 | KMeans_tall | fit | 5.728 | 0.018 | 1000000 | 1000000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 2.820 | 0.031 | 2.031 | 0.023 | See |
| 10 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.809 | 1.561 | See |
| 11 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.003 | 1.269 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 0.277 | 0.014 | 10000 | 10000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 29.0 | NaN | 0.097 | 0.002 | 2.847 | 0.158 | See |
| 1 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.749 | 1.392 | See |
| 2 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.065 | 0.379 | See |
| 3 | KMeans_short | fit | 0.107 | 0.001 | 10000 | 10000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.040 | 0.000 | 2.669 | 0.032 | See |
| 4 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.762 | 1.418 | See |
| 5 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.046 | 0.350 | See |
| 6 | KMeans_short | fit | 0.710 | 0.031 | 10000 | 10000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 17.0 | NaN | 21.0 | NaN | 0.333 | 0.010 | 2.131 | 0.113 | See |
| 7 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.699 | 1.346 | See |
| 8 | KMeans_short | predict | 0.006 | 0.002 | 10000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 4.977 | 2.400 | See |
| 9 | KMeans_short | fit | 0.230 | 0.035 | 10000 | 10000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 19.0 | NaN | 28.0 | NaN | 0.151 | 0.016 | 1.525 | 0.285 | See |
| 10 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.718 | 1.241 | See |
| 11 | KMeans_short | predict | 0.004 | 0.001 | 10000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 3.934 | 1.618 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 11.145 | 0.084 | 1000000 | 1000000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 11.381 | 0.037 | 0.979 | 0.008 | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.367 | 0.444 | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.851 | 0.512 | See |
| 3 | LogisticRegression | fit | 0.813 | 0.019 | 1000 | 1000 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [26] | 0.793 | 0.056 | 1.026 | 0.076 | See |
| 4 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.001 | 0.002 | 0.079 | 0.116 | See |
| 5 | LogisticRegression | predict | 0.002 | 0.000 | 1000 | 100 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.003 | 0.000 | 0.504 | 0.132 | See |
Shared hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1.706 | 0.035 | 100000 | 100000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.863 | 0.010 | 1.977 | 0.047 | See |
| 1 | Ridge | predict | 0.000 | 0.000 | 100000 | 1 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.492 | 0.555 | See |
| 2 | Ridge | predict | 0.001 | 0.000 | 100000 | 1000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.001 | 0.000 | 0.912 | 0.545 | See |
| 3 | Ridge | fit | 1.134 | 0.013 | 1000000 | 1000000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.225 | 0.002 | 5.046 | 0.080 | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.605 | 0.724 | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.659 | 0.533 | See |
Shared hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | False |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
{
"system_info": {
"python": "3.8.8 | packaged by conda-forge | (default, Feb 20 2021, 16:22:27) [GCC 9.3.0]",
"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1046-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
"pip": "21.1",
"setuptools": "49.6.0.post20210108",
"sklearn": "0.24.1",
"numpy": "1.20.2",
"scipy": "1.6.2",
"Cython": null,
"pandas": "1.2.4",
"matplotlib": null,
"joblib": "1.0.1",
"threadpoolctl": "2.1.0"
},
"threadpool_info": [
{
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"prefix": "libopenblas",
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"version": "0.3.12",
"num_threads": 2,
"threading_layer": "pthreads"
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libgomp.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
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}
],
"cpu_count": 2
}